Modeling the Snow Depth Variability with a High-Resolution Lidar Data Set and Nonlinear Terrain Dependency
by T. Skaugen & K. Melvold
Summary: Using airborne laser, 400 million snow depth measurements at Hardangervidda in Southern Norway have been collected. The amount of data has made in-depth studies of the spatial distribution of snow and its interaction with the terrain and vegetation possible. We find that the terrain variability, expressed by the square slope, the average amount of snow, and whether the terrain is vegetated or not, largely explains the variation of snow depth. With this information it is possible to develop equations that predict snow depth variability that can be used in environmental models, which again are used for important tasks such as flood forecasting and hydropower planning. One major advantage is that these equations can be determined from the data that are, in principle, available everywhere, provided there exists a detailed digital model of the terrain.
by Christine L. Dolph, Evelyn Boardman, Mohammad Danesh-Yazdi, Jacques C. Finlay, Amy T. Hansen, Anna C. Baker & Brent Dalzell
Abstract: When phosphorus from farm fertilizer, eroded soil, and septic waste enters our water, it leads to problems like toxic algae blooms, fish kills, and contaminated drinking supplies. In this study, we examine how phosphorus travels through streams and rivers of farmed areas. In the past, soil lost from farm fields was considered the biggest contributor to phosphorus pollution in agricultural areas, but our study shows that phosphorus originating from fertilizer stores in the soil and from crop residue, as well as from soil eroded from sensitive ravines and bluffs, contributes strongly to the total amount of phosphorus pollution in agricultural rivers. We also found that most phosphorus leaves farmed watersheds during the very highest river flows. Increased frequency of large storms due to climate chaos will therefore likely worsen water quality in areas that are heavily loaded with phosphorus from farm fertilizers. Protecting water in agricultural watersheds will require knowledge of the local landscape along with strategies to address (1) drivers of climate chaos, (2) reduction in the highest river flows, and (3) ongoing inputs and legacy stores of phosphorus that are readily transported across land and water.
Detecting the State of the Climate System via Artificial Intelligence to Improve Seasonal Forecasts and Inform Reservoir Operations
by Matteo Giuliani, Marta Zaniolo, Andrea Castelletti, Guido Davoli & Paul Block
Abstract: Increasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance. We apply the framework to the Lake Como basin, a regulated lake in northern Italy mainly operated for flood control and irrigation supply. Numerical results show the existence of notable teleconnection patterns dependent on both ENSO and the North Atlantic Oscillation over the Alpine region, which contribute in generating skillful seasonal precipitation and hydrologic forecasts. The use of this information for conditioning the lake operations produces an average 44% improvement in system performance with respect to a baseline solution not informed by any forecast, with this gain that further increases during extreme drought episodes. Our results also suggest that observed preseason sea surface temperature anomalies appear more valuable than hydrologic-based seasonal forecasts, producing an average 59% improvement in system performance.
Landscape Water Storage and Subsurface Correlation from Satellite Surface Soil Moisture and Precipitation Observations
by Daniel J. Short Gianotti, Guido D. Salvucci, Ruzbeh Akbar, Kaighin A. McColl, Richard Cuenca & Dara Entekhabi
Abstract: Surface soil moisture measurements are typically correlated to some degree with changes in subsurface soil moisture. We calculate a hydrologic length scale, λ, which represents (1) the mean-state estimator of total column water changes from surface observations, (2) an e-folding length scale for subsurface soil moisture profile covariance fall-off, and (3) the best second-moment mass-conserving surface layer thickness for a simple bucket model, defined by the data streams of satellite soil moisture and precipitation retrievals. Calculations are simple, based on three variables: the autocorrelation and variance of surface soil moisture and the variance of the net flux into the column (precipitation minus estimated losses), which can be estimated directly from the soil moisture and precipitation time series. We develop a method to calculate the lag-one autocorrelation for irregularly observed time series and show global surface soil moisture autocorrelation. λ is driven in part by local hydroclimate conditions and is generally larger than the 50-mm nominal radiometric length scale for the soil moisture retrievals, suggesting broad subsurface correlation due to moisture drainage. In all but the most arid regions, radiometric soil moisture retrievals provide more information about ecosystem-relevant water fluxes than satellite radiometers can explicitly “see”; lower-frequency radiometers are expected to provide still more statistical information about subsurface water dynamics.
by Jordan S. Read, Xiaowei Jia, Jared Willard, Alison P. Appling, Jacob A. Zwart, Samantha K. Oliver, Anuj Karpatne, Gretchen J. A. Hansen, Paul C. Hanson, William Watkins, Michael Steinbach & Vipin Kumar
Abstract: The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state-of-the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process-Guided Deep Learning (PGDL) hybrid modeling framework with a use-case of predicting depth-specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short-term memory recurrence), theory-based feedback (model penalties for violating conversation of energy), and model pre-training to initialize the network with synthetic data (water temperature predictions from a process-based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process-based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root-mean-square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case-study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.
Adjustment of Radar-Gauge Rainfall Discrepancy Due to Raindrop Drift and Evaporation Using the Weather Research and Forecasting Model and Dual-Polarization Radar
by Qiang Dai, Qiqi Yang, Dawei Han, Miguel A. Rico-Ramirez & Shuliang Zhang
Abstract: Radar-gauge rainfall discrepancies are considered to originate from radar rainfall measurements while ignoring the fact that radar observes rain aloft while a rain gauge measures rainfall on the ground. Observations of raindrops observed aloft by weather radars consider that raindrops fall vertically to the ground without changing in size. This premise obviously does not stand because raindrop location changes due to wind drift and raindrop size changes due to evaporation. However, both effects are usually ignored. This study proposes a fully formulated scheme to numerically simulate both raindrop drift and evaporation in the air and reduces the uncertainties of radar rainfall estimation. The Weather Research and Forecasting model is used to simulate high-resolution three-dimensional atmospheric fields. A dual-polarization radar retrieves the raindrop size distribution for each radar pixel. Three schemes are designed and implemented using the Hameldon Hill radar in Lancashire, England. The first considers only raindrop drift, the second considers only evaporation, and the last considers both aspects. Results show that wind advection can cause a large drift for small raindrops. Considerable loss of rainfall is observed due to raindrop evaporation. Overall, the three schemes improve the radar-gauge correlation by 3.2%, 2.9%, and 3.8% and reduce their discrepancy by 17.9%, 8.6%, and 21.7%, respectively, over eight selected events. This study contributes to the improvement of quantitative precipitation estimation from radar polarimetry and allows a better understanding of precipitation processes.
The Role of Collapsed Bank Soil on Tidal Channel Evolution: A Process-Based Model Involving Bank Collapse and Sediment Dynamics
by K. Zhao, Z. Gong, F. Xu, Z. Zhou, C. K. Zhang, G. M. E. Perillo & G. Coco
Abstract: We develop a process-based model to simulate the geomorphodynamic evolution of tidal channels, considering hydrodynamics, flow-induced bank erosion, gravity-induced bank collapse, and sediment dynamics. A stress-deformation analysis and the Mohr-Coulomb criterion, calibrated through previous laboratory experiments, are included in a model simulating bank collapse. Results show that collapsed bank soil plays a primary role in the dynamics of bank retreat. For bank collapse with small bank height, tensile failure in the middle of the bank (Stage I), tensile failure on the bank top (Stage II), and sectional cracking from bank top to the toe (Stage III) are present sequentially before bank collapse occurs. A significant linear relation is observed between bank height and the contribution of bank collapse to bank retreat. Contrary to flow-induced bank erosion, bank collapse prevents further widening since the collapsed bank soil protects the bank from direct bank erosion. The bank profile is linear or slightly convex, and the planimetric shape of tidal channels (gradually decreasing in width landward) is similar when approaching equilibrium, regardless of the consideration of bank erosion and collapse. Moreover, the simulated width-to-depth ratio in all runs is comparable with observations from the Venice Lagoon. This indicates that the equilibrium configuration of tidal channels depends on hydrodynamic conditions and sediment properties, while bank erosion and collapse greatly affect the transient behavior (before equilibrium) of the tidal channels. Overall, this contribution highlights the importance of collapsed bank soil in investigating tidal channel morphodynamics using a combined perspective of geotechnics and soil mechanics.
by Yunquan Wang, Oliver Merlin, Gaofeng Zhu & Kun Zhang
Abstract: While numerous models exist for soil evaporation estimation, they are more or less empirically based either in the model structure or in the determination of introduced parameters. The main difficulty lies in representing the water stress factor, which is usually thought to be limited by capillarity-supported water supply or by vapor diffusion flux. Recent progress in understanding soil hydraulic properties, however, have found that the film flow, which is often neglected, is the dominant process under low moisture conditions. By including the impact of film flow, a reexamination on the typical evaporation process found that this usually neglected film flow might be the dominant process for supporting the Stage II evaporation (i.e., the fast falling rate stage), besides the generally accepted capillary flow-supported Stage I evaporation and the vapor diffusion-controlled Stage III evaporation. A physically based model for estimating the evaporation rate was then developed by parameterizing the Buckingham-Darcy’s law. Interestingly, the empirical Bucket model was found to be a specific form of the proposed model. The proposed model requires the in-equilibrium relative humidity as the sole input for representing water stress and introduces no adjustable parameter in relation to soil texture. The impact of vapor diffusion was also discussed. Model testing with laboratory data yielded an excellent agreement with observations for both thin soil and thick soil column evaporation experiments. Model evaluation at 15 field sites generally showed a close agreement with observations, with a great improvement in the lower range of evaporation rates in comparison with the widely applied Priestley and Taylor Jet Propulsion Laboratory model.
Floodplain Land Cover and Flow Hydrodynamic Control of Overbank Sedimentation in Compound Channel Flows
by Carmelo Juez, C. Schärer, H. Jenny, A. J. Schleiss & M. J. Franca
Abstract: Overbank sedimentation is predominantly due to fine sediments transported under suspension that become trapped and settle in floodplains when high-flow conditions occur in rivers. In a compound channel, the processes of exchanging water and fine sediments between the main channel and floodplains regulate the geomorphological evolution and are crucial for the maintenance of the ecosystem functions of the floodplains. These hydrodynamic and morphodynamic processes depend on variables such as the flow-depth ratio between the water depth in the main channel and the water depth in the floodplain, the width ratio between the width of the main channel and the width of the floodplain, and the floodplain land cover characterized by the type of roughness. This paper examines, by means of laboratory experiments, how these variables are interlinked and how the deposition of sediments in the compound channel is jointly determined by them. The combination of these compound channel characteristics modulates the production of vertically axised large turbulent vortical structures in the mixing interface. Such vortical structures determine the water mass exchange between the main channel and the floodplain, conditioning in turn the transport of sediment particles conveyed in the water, and, therefore, the resulting overbank sedimentation. The existence and pattern of sedimentation are conditioned by both the hydrodynamic variables (the flow-depth ratio and the width ratio) and the floodplain land cover simulated in terms of smooth walls, meadow-type roughness, sparse-wood-type roughness, and dense-wood-type roughness.
Identifying Actionable Compromises: Navigating Multi-city Robustness Conflicts to Discover Cooperative Safe Operating Spaces for Regional Water Supply Portfolios
by D. F. Gold, P. M. Reed, B. C. Trindade & G. W. Characklis
Summary: Cooperation among neighboring urban water utilities can help water managers face challenges stemming from climate change and population growth. Water utilities can cooperate by coordinating water transfers and water restrictions in times of water scarcity (drought) so that water is provided to areas that need it most. In order to successfully implement these policies, however, cooperative partners must find a compromise that is acceptable to all regional actors, a task complicated by asymmetries in resources and risks often present in regional systems. The possibility of deviations from agreed upon actions is another complicating factor that has not been addressed in water resources literature. Our study focuses on four urban water utilities in the Research Triangle region of North Carolina who are investigating cooperative drought mitigation strategies. We contribute a framework that includes the use of simulation models, optimization algorithms, and statistical tools to aid cooperating partners in finding acceptable compromises that are tolerant modest deviations in planned actions. Our results can be used by regional utilities to avoid or alleviate potential planning conflicts and are broadly applicable to urban regional water supply planning across the globe.
Detecting Changes in River Flow Caused by Wildfires, Storms, Urbanization, Regulation, and Climate across Sweden
by Berit Arheimer & Göran Lindström
Abstract: Changes in river flow may appear from shifts in land cover, constructions in the river channel, and climatic change, but currently there is a lack of understanding of the relative importance of these drivers. Therefore, we collected gauged river flow time series from 1961 to 2018 from across Sweden for 34 disturbed catchments to quantify how the various types of disturbances have affected river flow. We used trend analysis and the differences in observations versus hydrological modeling to explore the effects on river flow from (1) land cover changes from wildfires, storms, and urbanization; (2) dam constructions with regulations for hydropower production; and (3) climate-change impact in otherwise undisturbed catchments. A mini model ensemble, consisting of three versions of the S-HYPE model, was used, and the three models gave similar results. We searched for changes in annual and daily stream flow, seasonal flow regime, and flow duration curves. The results show that regulation of river flow has the largest impact, reducing spring floods with up to 100% and increasing winter flow by several orders of magnitude, with substantial effects transmitted far downstream. Climate changed the total river flow up to 20%. Tree removal by wildfires and storms has minor impacts at medium and large scales. Urbanization, on the contrary, showed a 20% increase in high flows also at medium scales. This study emphasizes the benefits of combining observed time series with numerical modeling to exclude the effect of varying weather conditions, when quantifying the effects of various drivers on long-term streamflow shifts.
by Matthew A. Thomas, Brian D. Collins & Benjamin B. Mirus
Summary: Soil wetness and rainfall contribute to landslides across the world. Using soil moisture sensors and rain gauges, these environmental conditions have been monitored at numerous points across the Earth’s surface to define threshold conditions, above which landsliding should be expected for a localized area. Satellite-based technologies also deliver estimates of soil wetness and rainfall, potentially offering an approach to develop thresholds as part of landslide warning systems over larger spatial scales. To evaluate the potential for using satellite-based measurements for landslide warning, we compare the accuracy of landslide thresholds defined with ground- versus satellite-based soil wetness and rainfall information. We find that the satellite-based data over-predict soil wetness during the time of year when landslides are most likely to occur, resulting in thresholds that also over-predict the potential for landslides relative to thresholds informed by direct measurements on the ground. Our results encourage the installation of more ground-based monitoring stations in landslide-prone settings and the cautious use of satellite-based data when more direct measurements are not available.
Modeling the Translocation and Transformation of Chemicals in the Soil-Plant Continuum: A Dynamic Plant Uptake Module for the HYDRUS Model
by Giuseppe Brunetti, Radka Kodešová & Jiří Šimůnek
Abstract: Food contamination is responsible for thousands of deaths worldwide every year. Plants represent the most common pathway for chemicals into the human and animal food chain. Although existing dynamic plant uptake models for chemicals are crucial for the development of reliable mitigation strategies for food pollution, they nevertheless simplify the description of physicochemical processes in soil and plants, mass transfer processes between soil and plants and in plants, and transformation in plants. To fill this scientific gap, we couple a widely used hydrological model (HYDRUS) with a multi-compartment dynamic plant uptake model, which accounts for differentiated multiple metabolization pathways in plant’s tissues. The developed model is validated first theoretically and then experimentally against measured data from an experiment on the translocation and transformation of carbamazepine in three vegetables. The analysis is further enriched by performing a global sensitivity analysis on the soil–plant model to identify factors driving the compound’s accumulation in plants’ shoots, as well as to elucidate the role and the importance of soil hydraulic properties on the plant uptake process. Results of the multilevel numerical analysis emphasize the model’s flexibility and demonstrate its ability to accurately reproduce physicochemical processes involved in the dynamic plant uptake of chemicals from contaminated soils.
Physical Controls on Salmon Redd Site Selection in Restored Reaches of a Regulated, Gravel-Bed River
by Lee R. Harrison, Erin Bray, Brandon Overstreet, Carl J. Legleiter, Rocko A. Brown, Joseph E. Merz, Rosealea M. Bond, Colin L. Nicol & Thomas Dunne
Abstract: Large-scale river restoration programs have emerged recently as a tool for improving spawning habitat for native salmonids in highly altered river ecosystems. Few studies have quantified the extent to which restored habitat is utilized by salmonids, which habitat features influence redd site selection, or the persistence of restored habitat over time. We investigated fall-run Chinook salmon spawning site utilization and measured and modeled corresponding habitat characteristics in two restored reaches: a reach of channel and floodplain enhancement completed in 2013 and a reconfigured channel and floodplain constructed in 2002. Redd surveys demonstrated that both restoration projects supported a high density of salmon redds, 3 and 14 years following restoration. Salmon redds were constructed in coarse gravel substrates located in areas of high sediment mobility, as determined by measurements of gravel friction angles and a grain entrainment model. Salmon redds were located near transitions between pool-riffle bedforms in regions of high predicted hyporheic flows. Habitat quality (quantified as a function of stream hydraulics) and hyporheic flow were both strong predictors of redd occurrence, though the relative roles of these variables differed between sites. Our findings indicate that physical controls on redd site selection in restored channels were similar to those reported for natural channels elsewhere. Our results further highlight that in addition to traditional habitat criteria (e.g., water depth, velocity, and substrate size), quantifying sediment texture and mobility, as well as intragravel flow, provides a more complete understanding of the ecological benefits provided by river restoration projects.
by Katherine H. Markovich, Andrew H. Manning, Laura E. Condon & Jennifer C. McIntosh
Abstract: Mountain-block recharge (MBR) is the subsurface inflow of groundwater to lowland aquifers from adjacent mountains. MBR can be a major component of recharge but remains difficult to characterize and quantify due to limited hydrogeologic, climatic, and other data in the mountain block and at the mountain front. The number of MBR-related studies has increased dramatically in the 15 years since the last review of the topic was conducted by Wilson and Guan (2004), generating important advancements. We review this recent body of literature, summarize current understanding of factors controlling MBR, and provide recommendations for future research priorities. Prior to 2004, most MBR studies were performed in the southwestern United States. Since then, numerous studies have detected and quantified MBR in basins around the world, typically estimating MBR to be 5–50% of basin-fill aquifer recharge. Theoretical studies using generic numerical modeling domains have revealed fundamental hydrogeologic and topographic controls on the amount of MBR and where it originates within the mountain block. Several mountain-focused hydrogeologic studies have confirmed the widespread existence of mountain bedrock aquifers hosting considerable groundwater flow and, in some cases, identified the occurrence of interbasin flow leaving headwater catchments in the subsurface—both of which are required for MBR to occur. Future MBR research should focus on the collection of high-priority data (e.g., subsurface data near the mountain front and within the mountain block) and the development of sophisticated coupled models calibrated to multiple data types to best constrain MBR and predict how it may change in response to climate warming.
An Adjoint Sensitivity Model for Steady-State Sequentially Coupled Radionuclide Transport in Porous Media
by Mohamed Hayek, Banda S. RamaRao & Marsh Lavenue
Abstract: This work presents an efficient mathematical/numerical model to compute the sensitivity coefficients of a predefined performance measure to model parameters for one-dimensional steady-state sequentially coupled radionuclide transport in a finite heterogeneous porous medium. The model is based on the adjoint sensitivity approach that offers an elegant and computationally efficient alternative way to compute the sensitivity coefficients. The transport parameters include the radionuclide retardation factors due to sorption, the Darcy velocity, and the effective diffusion/dispersion coefficients. Both continuous and discrete adjoint approaches are considered. The partial differential equations associated with the adjoint system are derived based on the adjoint state theory for coupled problems. Physical interpretations of the adjoint states are given in analogy to results obtained in the theory of groundwater flow. For the homogeneous case, analytical solutions for primary and adjoint systems are derived and presented in closed forms. Numerically calculated solutions are compared to the analytical results and show excellent agreements. Insights from sensitivity analysis are discussed to get a better understanding of the values of sensitivity coefficients. The sensitivity coefficients are also computed numerically by finite differences. The numerical sensitivity coefficients successfully reproduce the analytically derived sensitivities based on adjoint states. A derivative-based global sensitivity method coupled with the adjoint state method is presented and applied to a real field case represented by a site currently being considered for underground nuclear storage in Northern Switzerland, “Zürich Nordost,” to demonstrate the proposed method. The results show the advantage of the adjoint state method compared to other methods in term of computational effort.
by C. Ancey, E. Bardou, M. Funk, M. Huss, M. A. Werder & T. Trewhela
Summary: Every year, natural and man-made dams fail and cause flooding. For public authorities, estimating the risk posed by dams is essential to good risk management. Efficient computational tools are required for analyzing flood risk. Testing these tools is an important step toward ensuring their reliability and performance. Knowledge of major historical floods makes it possible, in principle, to benchmark models, but because historical data are often incomplete and fraught with potential inaccuracies, validation is seldom satisfactory. Here we present one of the few major historical floods for which information on flood initiation and propagation is available and detailed: the Giétro flood. This flood occurred in June 1818 and devastated the Drance Valley in Switzerland. In the spring of that year, ice avalanches blocked the valley floor and formed a glacial lake, whose volume is today estimated at 25×106 m3. The local authorities initiated protection works: A tunnel was drilled through the ice dam, and about half of the stored water volume was drained in 2.5 days. On 16 June 1818, the dam failed suddenly because of significant erosion at its base; this caused a major flood. This paper presents a numerical model for estimating flow rates, velocities, and depths during the dam drainage and flood flow phases. The numerical results agree well with historical data. The flood reconstruction shows that relatively simple models can be used to estimate the effects of a major flood with good accuracy.
by Marialaura Bancheri, Francesco Serafin & Riccardo Rigon
Abstract: This work presents a new graphical system to represent hydrological dynamical models and their interactions. We propose an extended version of the Petri Nets mathematical modeling language, the Extended Petri Nets (EPN), which allows for an immediate translation from the graphics of the model to its mathematical representation in a clear way. We introduce the principal objects of the EPN representation (i.e., places, transitions, arcs, controllers, and splitters) and their use in hydrological systems. We show how to cast hydrological models in EPN and how to complete their mathematical description using a dictionary for the symbols and an expression table for the flux equations. Thanks to the compositional property of EPN, we show how it is possible to represent either a single hydrological response unit or a complex catchment where multiple systems of equations are solved simultaneously. Finally, EPN can be used to describe complex Earth system models that include feedback between the water, energy, and carbon budgets. The representation of hydrological dynamical systems with EPN provides a clear visualization of the relations and feedback between subsystems, which can be studied with techniques introduced in nonlinear systems theory and control theory.
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A Regularization Approach to Improve the Sequential Calibration of a Semidistributed Hydrological Model
by A. de Lavenne, V. Andréassian, G. Thirel, M.-H. Ramos & C. Perrin
Abstract: In semidistributed hydrological modeling, sequential calibration usually refers to the calibration of a model by considering not only the flows observed at the outlet of a catchment but also the different gauging points inside the catchment from upstream to downstream. While sequential calibration aims to optimize the performance at these interior gauged points, we show that it generally fails to improve performance at ungauged points. In this paper, we propose a regularization approach for the sequential calibration of semidistributed hydrological models. It consists in adding a priori information on optimal parameter sets for each modeling unit of the semi-distributed model. Calibration iterations are then performed by jointly maximizing simulation performance and minimizing drifts from the a priori parameter sets. The combination of these two sources of information is handled by a parameter k to which the method is quite sensitive. The method is applied to 1,305 catchments in France over 30 years. The leave-one-out validation shows that, at locations considered as ungauged, model simulations are significantly improved (over all the catchments, the median KGE criterion is increased from 0.75 to 0.83 and the first quartile from 0.35 to 0.66), while model performance at gauged points is not significantly impacted by the use of the regularization approach. Small catchments benefit most from this calibration strategy. These performances are, however, very similar to the performances obtained with a lumped model based on similar conceptualization.
by Manuela I. Brunner & Lena M. Tallaksen
Summary: Droughts lasting longer than 1 year can have severe ecological, social, and economic impacts. They are characterized by below-average flows, not only during the low-flow period but also in the high-flow period when water stores such as groundwater or artificial reservoirs are usually replenished. Limited catchment storage might worsen the impacts of droughts and make water management more challenging. Knowledge on the occurrence of multiyear drought events enables better adaptation and increases preparedness. In this study, we assess the proneness of European catchments to multiyear droughts by simulating long discharge records. Our findings show that multiyear drought events mainly occur in regions where the discharge seasonality is mostly influenced by rainfall, whereas catchments whose seasonality is dominated by melt processes are less affected. The strong link between the proneness of a catchment to multiyear events and its discharge seasonality leads to the conclusion that future changes toward less snow storage and thus less snow melt will increase the probability of multiyear drought occurrence.
Equifinality and Flux Mapping: A New Approach to Model Evaluation and Process Representation under Uncertainty
by Sina Khatami, Murray C. Peel, Tim J. Peterson & Andrew W. Western
Abstract: Uncertainty analysis is an integral part of any scientific modeling, particularly within the domain of hydrological sciences given the various types and sources of uncertainty. At the center of uncertainty rests the concept of equifinality, that is, reaching a given endpoint (finality) through different pathways. The operational definition of equifinality in hydrological modeling is that various model structures and/or parameter sets (i.e., equal pathways) are equally capable of reproducing a similar (not necessarily identical) hydrological outcome (i.e., finality). Here we argue that there is more to model equifinality than model structures/parameters, that is, other model components can give rise to model equifinality and/or could be used to explore equifinality within model space. We identified six facets of model equifinality, namely, model structure, parameters, performance metrics, initial and boundary conditions, inputs, and internal fluxes. Focusing on model internal fluxes, we developed a methodology called flux mapping that has fundamental implications in understanding and evaluating model process representation within the paradigm of multiple working hypotheses. To illustrate this, we examine the equifinality of runoff fluxes of a conceptual rainfall-runoff model for a number of different Australian catchments. We demonstrate how flux maps can give new insights into the model behavior that cannot be captured by conventional model evaluation methods. We discuss the advantages of flux space, as a subspace of the model space not usually examined, over parameter space. We further discuss the utility of flux mapping in hypothesis generation and testing, extendable to any field of scientific modeling of open complex systems under uncertainty.
Role of Extreme Precipitation and Initial Hydrologic Conditions on Floods in Godavari River Basin, India
by Shailesh Garg & Vimal Mishra
Abstract: Floods are the most frequent natural calamity in India. The Godavari river basin (GRB) witnessed several floods in the past 50 years. Notwithstanding the large damage and economic loss, the role of extreme precipitation and antecedent moisture conditions on floods in the GRB remains unexplored. Using the observations and the well-calibrated Variable Infiltration Capacity model, we estimate the changes in the extreme precipitation and floods in the observed (1955–2016) and projected future (2071–2100) climate in the GRB. We evaluate the role of initial hydrologic conditions and extreme precipitation on floods in both observed and projected future climate. We find a statistically significant increase in annual maximum precipitation for the catchments upstream of four gage stations during the 1955–2016 period. However, the rise in annual maximum streamflow at all the four gage stations in GRB was not statistically significant. The probability of floods driven by extreme precipitation (PFEP) varies between 0.55 and 0.7 at the four gage stations of the GRB, which declines with the size of the basins. More than 80% of extreme precipitation events that cause floods occur on wet antecedent moisture conditions at all the four locations in the GRB. The frequency of extreme precipitation events is projected to rise by two folds or more (under RCP 8.5) in the future (2071–2100) at all four locations. However, the increased frequency of floods under the future climate will largely be driven by the substantial rise in the extreme precipitation events rather than wet antecedent moisture conditions.
Combined Effect of Tides and Varying Inland Groundwater Input on Flow and Salinity Distribution in Unconfined Coastal Aquifers
by Woei Keong Kuan, Pei Xin, Guangqiu Jin, Clare E. Robinson, Badin Gibbes & Ling Li
Abstract: Tides and seasonally varying inland freshwater input, with different fluctuation periods, are important factors affecting flow and salt transport in coastal unconfined aquifers. These processes affect submarine groundwater discharge (SGD) and associated chemical transport to the sea. While the individual effects of these forcings have previously been studied, here we conducted physical experiments and numerical simulations to evaluate the interactions between varying inland freshwater input and tidal oscillations. Varying inland freshwater input was shown to induce significant water exchange across the aquifer-sea interface as the saltwater wedge shifted landward and seaward over the fluctuation cycle. Tidal oscillations led to seawater circulations through the intertidal zone that also enhanced the density-driven circulation, resulting in a significant increase in the total SGD. The combination of the tide and varying inland freshwater input, however, decreased the SGD components driven by the separate forcings (e.g., tides and density). Tides restricted the landward and seaward movement of the saltwater wedge in response to the varying inland freshwater input in addition to reducing the time delay between the varying freshwater input signal and landward-seaward movement in the saltwater wedge interface. This study revealed the nonlinear interaction between tidal fluctuations and varying inland freshwater input will help to improve our understanding of SGD, seawater intrusion, and chemical transport in coastal unconfined aquifers.